This paper proposes a novel view in the race and causation literature known as “causal agnosticism” about race. Causal agnosticism about race implies that it is reasonable to refrain from making judgments about whether race is a cause. The paper’s thesis asserts that certain conditions must be met to infer that something is a cause, according to the fundamental assumptions of causal inference. However, in the case of race, these conditions are often violated. By advocating for causal agnosticism, the paper suggests a more modest approach to understanding the role of race in causal relationships.
{"title":"Causal Agnosticism About Race: Variable Selection Problems in Causal Inference","authors":"Alexander Tolbert","doi":"10.1017/psa.2023.166","DOIUrl":"https://doi.org/10.1017/psa.2023.166","url":null,"abstract":"\u0000 This paper proposes a novel view in the race and causation literature known as “causal agnosticism” about race. Causal agnosticism about race implies that it is reasonable to refrain from making judgments about whether race is a cause. The paper’s thesis asserts that certain conditions must be met to infer that something is a cause, according to the fundamental assumptions of causal inference. However, in the case of race, these conditions are often violated. By advocating for causal agnosticism, the paper suggests a more modest approach to understanding the role of race in causal relationships.","PeriodicalId":54620,"journal":{"name":"Philosophy of Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139961679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Bayesian agents, argues Belot (2013), are orgulous: they believe in inductive success even when guaranteed to fail on a topologically typical collection of data streams. Here we shed light on how pervasive this phenomenon is. We identify several classes of inductive problems for which Bayesian convergence to the truth is topologically typical. However, we also show that, for all sufficiently complex classes, there are inductive problems for which convergence is topologically atypical. Lastly, we identify specific topologically typical collections of data streams, observing which guarantees convergence to the truth across all problems from certain natural classes of effective inductive problems.
{"title":"Pride and Probability","authors":"Francesca Zaffora Blando","doi":"10.1017/psa.2023.177","DOIUrl":"https://doi.org/10.1017/psa.2023.177","url":null,"abstract":"Abstract\u0000 Bayesian agents, argues Belot (2013), are orgulous: they believe in inductive success even when guaranteed to fail on a topologically typical collection of data streams. Here we shed light on how pervasive this phenomenon is. We identify several classes of inductive problems for which Bayesian convergence to the truth is topologically typical. However, we also show that, for all sufficiently complex classes, there are inductive problems for which convergence is topologically atypical. Lastly, we identify specific topologically typical collections of data streams, observing which guarantees convergence to the truth across all problems from certain natural classes of effective inductive problems.","PeriodicalId":54620,"journal":{"name":"Philosophy of Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139594750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Imagine that we are on a train playing with some mechanical systems. Why can’t we detect any differences in their behavior when the train is parked versus when it is moving uniformly? The standard answer is that boosts are symmetries of Newtonian systems. In this paper, I use the case of a spring to argue that this answer is problematic because symmetries are neither sufficient nor necessary for preserving its behavior. I also develop a new answer according to which boosts preserve the relational properties on which the behavior of a system depends, even when they are not symmetries.
{"title":"On Symmetries and Springs","authors":"Sebastián Murgueitio Ramírez","doi":"10.1017/psa.2023.170","DOIUrl":"https://doi.org/10.1017/psa.2023.170","url":null,"abstract":"\u0000 Imagine that we are on a train playing with some mechanical systems. Why can’t we detect any differences in their behavior when the train is parked versus when it is moving uniformly? The standard answer is that boosts are symmetries of Newtonian systems. In this paper, I use the case of a spring to argue that this answer is problematic because symmetries are neither sufficient nor necessary for preserving its behavior. I also develop a new answer according to which boosts preserve the relational properties on which the behavior of a system depends, even when they are not symmetries.","PeriodicalId":54620,"journal":{"name":"Philosophy of Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139598100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Ernest Nagel: Philosophy of Science and the Fight for Clarity. Matthias Neuber and Adam Tamas Tuboly, eds. Cham, Switzerland: Springer, 2022","authors":"Don Howard","doi":"10.1017/psa.2024.1","DOIUrl":"https://doi.org/10.1017/psa.2024.1","url":null,"abstract":"","PeriodicalId":54620,"journal":{"name":"Philosophy of Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139596287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Well-known debates among statistical inferential paradigms emerge from conflicting views on the notion of probability. One dominant view understands probability as a representation of sampling variability, another prominent view understands probability as a measure of belief. The former generally describes model parameters as fixed values, in contrast to the latter. We propose there are actually two versions of a parameter within both paradigms: a fixed, unknown value which generated the data and a random version to describe the uncertainty in estimating the unknown value. An inferential approach based on confidence distributions deciphers seemingly conflicting perspectives on parameters and probabilities.
{"title":"An exploration of parameter duality in statistical inference","authors":"S. Thornton, M. Xie","doi":"10.1017/psa.2023.174","DOIUrl":"https://doi.org/10.1017/psa.2023.174","url":null,"abstract":"\u0000 Well-known debates among statistical inferential paradigms emerge from conflicting views on the notion of probability. One dominant view understands probability as a representation of sampling variability, another prominent view understands probability as a measure of belief. The former generally describes model parameters as fixed values, in contrast to the latter. We propose there are actually two versions of a parameter within both paradigms: a fixed, unknown value which generated the data and a random version to describe the uncertainty in estimating the unknown value. An inferential approach based on confidence distributions deciphers seemingly conflicting perspectives on parameters and probabilities.","PeriodicalId":54620,"journal":{"name":"Philosophy of Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138973288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scientists and philosophers alike debate whether various systems such as plants and bacteria exercise cognition. One strategy for resolving such debates is to ground claims about nonhuman cognition in evidence from mathematical models of cognitive capacities. In this paper, I show that proponents of this strategy face two major challenges: demarcating phenomenological models from process models and overcoming underdetermination by model fit. I argue that even if the demarcation problem is resolved, fitting a process model to behavioral data is, on its own, not strong evidence for any cognitive process, let alone processes shared with humans.
{"title":"On Cognitive Modeling and Other Minds","authors":"J.P. Gamboa","doi":"10.1017/psa.2023.168","DOIUrl":"https://doi.org/10.1017/psa.2023.168","url":null,"abstract":"\u0000 Scientists and philosophers alike debate whether various systems such as plants and bacteria exercise cognition. One strategy for resolving such debates is to ground claims about nonhuman cognition in evidence from mathematical models of cognitive capacities. In this paper, I show that proponents of this strategy face two major challenges: demarcating phenomenological models from process models and overcoming underdetermination by model fit. I argue that even if the demarcation problem is resolved, fitting a process model to behavioral data is, on its own, not strong evidence for any cognitive process, let alone processes shared with humans.","PeriodicalId":54620,"journal":{"name":"Philosophy of Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138973234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Imitating nature is an ever more popular strategy in many fields of science and engineering research, from ecological engineering to artificial intelligence. But while biomimetics and related fields have recently attracted increased attention from philosophers, there has been relatively little engagement with what I suggest we see as their basic epistemological presupposition: that we may acquire knowledge from nature. I argue that emphasizing and exploring this presupposition opens up a new approach to epistemology, based on a shift from a conventional epistemological relationship to nature as object of knowledge to a biomimetic relationship to nature as source of knowledge.
{"title":"Biomimetic Epistemology","authors":"Henry Dicks","doi":"10.1017/psa.2023.173","DOIUrl":"https://doi.org/10.1017/psa.2023.173","url":null,"abstract":"\u0000 Imitating nature is an ever more popular strategy in many fields of science and engineering research, from ecological engineering to artificial intelligence. But while biomimetics and related fields have recently attracted increased attention from philosophers, there has been relatively little engagement with what I suggest we see as their basic epistemological presupposition: that we may acquire knowledge from nature. I argue that emphasizing and exploring this presupposition opens up a new approach to epistemology, based on a shift from a conventional epistemological relationship to nature as object of knowledge to a biomimetic relationship to nature as source of knowledge.","PeriodicalId":54620,"journal":{"name":"Philosophy of Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138971362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An influential heuristic for thinking about climate adaptation asserts that “natural” adaptation strategies are the best ones. This heuristic has been roundly criticized but is difficult to dislodge in the absence of an alternative. We introduce a new heuristic that assesses adaptation strategies by looking at their maturity, power, and commitment. Maturity is the extent to which we understand an adaptation strategy’s effects. Power is the size of the effect an adaptation strategy will have. Commitment is the degree to which an adaptation strategy is difficult to test or reverse.
{"title":"A New Heuristic for Climate Adaptation","authors":"Kate Nicole Hoffman, K. Kovaka","doi":"10.1017/psa.2023.163","DOIUrl":"https://doi.org/10.1017/psa.2023.163","url":null,"abstract":"\u0000 An influential heuristic for thinking about climate adaptation asserts that “natural” adaptation strategies are the best ones. This heuristic has been roundly criticized but is difficult to dislodge in the absence of an alternative. We introduce a new heuristic that assesses adaptation strategies by looking at their maturity, power, and commitment. Maturity is the extent to which we understand an adaptation strategy’s effects. Power is the size of the effect an adaptation strategy will have. Commitment is the degree to which an adaptation strategy is difficult to test or reverse.","PeriodicalId":54620,"journal":{"name":"Philosophy of Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139001991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Two types of formal models—landscape search tasks and two-armed bandit models—are often used to study the effects that various social factors have on epistemic performance. I argue that they can be understood within a single framework. In this unified framework, I develop a model that may be used to understand the effects of functional and demographic diversity and their interaction. Using the unified model, I find that the benefit of demographic diversity is most pronounced in a functionally homogeneous group, and decreases with the increase of functional diversity.
{"title":"Landscapes and Bandits: A Unified Model of Functional and Demographic Diversity","authors":"Alice C.W. Huang","doi":"10.1017/psa.2023.169","DOIUrl":"https://doi.org/10.1017/psa.2023.169","url":null,"abstract":"\u0000 Two types of formal models—landscape search tasks and two-armed bandit models—are often used to study the effects that various social factors have on epistemic performance. I argue that they can be understood within a single framework. In this unified framework, I develop a model that may be used to understand the effects of functional and demographic diversity and their interaction. Using the unified model, I find that the benefit of demographic diversity is most pronounced in a functionally homogeneous group, and decreases with the increase of functional diversity.","PeriodicalId":54620,"journal":{"name":"Philosophy of Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138972548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper examines constraints and their role in scientific explanation. Common views in the philosophical literature suggest that constraints are non-causal and that they provide non-causal explanations. While much of this work focuses on examples from physics, this paper explores constraints from other fields, including neuroscience, physiology, and the social sciences. I argue that these cases involve constraints that are causal and that provide a unique type of causal explanation. This paper clarifies what it means for a factor to be a constraint, when such constraints are causal, and how they figure in scientific explanation.
{"title":"Causal Constraints in the Life and Social Sciences","authors":"Lauren Ross","doi":"10.1017/psa.2023.165","DOIUrl":"https://doi.org/10.1017/psa.2023.165","url":null,"abstract":"\u0000 This paper examines constraints and their role in scientific explanation. Common views in the philosophical literature suggest that constraints are non-causal and that they provide non-causal explanations. While much of this work focuses on examples from physics, this paper explores constraints from other fields, including neuroscience, physiology, and the social sciences. I argue that these cases involve constraints that are causal and that provide a unique type of causal explanation. This paper clarifies what it means for a factor to be a constraint, when such constraints are causal, and how they figure in scientific explanation.","PeriodicalId":54620,"journal":{"name":"Philosophy of Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138602374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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